As shown in Table REF , we first prepare a contributor metrics data that will be used as features for the TDA mapper.
This data contains 6 metrics that pertain to the different activities for each system from the 2,170 Gerrit contributors described in Section REF .
We use the Knotter tool,https://github.com/rosinality/knotter
which is an implementation of mapper algorithm and the t-Distributed Stochastic Neighbor Embedding (t-SNE)[1]}, a technique for dimensional reduction
and clustering, and our defined features as the filters for the visualization construction.
